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  <h1>Source code for nlp_architect.common.core_nlp_doc</h1><div class="highlight"><pre>
<span></span><span class="c1"># ******************************************************************************</span>
<span class="c1"># Copyright 2017-2018 Intel Corporation</span>
<span class="c1">#</span>
<span class="c1"># Licensed under the Apache License, Version 2.0 (the &quot;License&quot;);</span>
<span class="c1"># you may not use this file except in compliance with the License.</span>
<span class="c1"># You may obtain a copy of the License at</span>
<span class="c1">#</span>
<span class="c1">#     http://www.apache.org/licenses/LICENSE-2.0</span>
<span class="c1">#</span>
<span class="c1"># Unless required by applicable law or agreed to in writing, software</span>
<span class="c1"># distributed under the License is distributed on an &quot;AS IS&quot; BASIS,</span>
<span class="c1"># WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.</span>
<span class="c1"># See the License for the specific language governing permissions and</span>
<span class="c1"># limitations under the License.</span>
<span class="c1"># ******************************************************************************</span>
<span class="kn">import</span> <span class="nn">json</span>


<div class="viewcode-block" id="merge_punct_tok"><a class="viewcode-back" href="../../../generated_api/nlp_architect.common.html#nlp_architect.common.core_nlp_doc.merge_punct_tok">[docs]</a><span class="k">def</span> <span class="nf">merge_punct_tok</span><span class="p">(</span><span class="n">merged_punct_sentence</span><span class="p">,</span> <span class="n">last_merged_punct_index</span><span class="p">,</span> <span class="n">punct_text</span><span class="p">,</span> <span class="n">is_traverse</span><span class="p">):</span>
    <span class="c1"># merge the text of the punct tok</span>
    <span class="k">if</span> <span class="n">is_traverse</span><span class="p">:</span>
        <span class="n">merged_punct_sentence</span><span class="p">[</span><span class="n">last_merged_punct_index</span><span class="p">][</span><span class="s2">&quot;text&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
            <span class="n">punct_text</span> <span class="o">+</span> <span class="n">merged_punct_sentence</span><span class="p">[</span><span class="n">last_merged_punct_index</span><span class="p">][</span><span class="s2">&quot;text&quot;</span><span class="p">]</span>
        <span class="p">)</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">merged_punct_sentence</span><span class="p">[</span><span class="n">last_merged_punct_index</span><span class="p">][</span><span class="s2">&quot;text&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
            <span class="n">merged_punct_sentence</span><span class="p">[</span><span class="n">last_merged_punct_index</span><span class="p">][</span><span class="s2">&quot;text&quot;</span><span class="p">]</span> <span class="o">+</span> <span class="n">punct_text</span>
        <span class="p">)</span></div>


<div class="viewcode-block" id="find_correct_index"><a class="viewcode-back" href="../../../generated_api/nlp_architect.common.html#nlp_architect.common.core_nlp_doc.find_correct_index">[docs]</a><span class="k">def</span> <span class="nf">find_correct_index</span><span class="p">(</span><span class="n">orig_gov</span><span class="p">,</span> <span class="n">merged_punct_sentence</span><span class="p">):</span>
    <span class="k">for</span> <span class="n">tok_index</span><span class="p">,</span> <span class="n">tok</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">merged_punct_sentence</span><span class="p">):</span>
        <span class="k">if</span> <span class="p">(</span>
            <span class="n">tok</span><span class="p">[</span><span class="s2">&quot;start&quot;</span><span class="p">]</span> <span class="o">==</span> <span class="n">orig_gov</span><span class="p">[</span><span class="s2">&quot;start&quot;</span><span class="p">]</span>
            <span class="ow">and</span> <span class="n">tok</span><span class="p">[</span><span class="s2">&quot;len&quot;</span><span class="p">]</span> <span class="o">==</span> <span class="n">orig_gov</span><span class="p">[</span><span class="s2">&quot;len&quot;</span><span class="p">]</span>
            <span class="ow">and</span> <span class="n">tok</span><span class="p">[</span><span class="s2">&quot;pos&quot;</span><span class="p">]</span> <span class="o">==</span> <span class="n">orig_gov</span><span class="p">[</span><span class="s2">&quot;pos&quot;</span><span class="p">]</span>
            <span class="ow">and</span> <span class="n">tok</span><span class="p">[</span><span class="s2">&quot;text&quot;</span><span class="p">]</span> <span class="o">==</span> <span class="n">orig_gov</span><span class="p">[</span><span class="s2">&quot;text&quot;</span><span class="p">]</span>
        <span class="p">):</span>
            <span class="k">return</span> <span class="n">tok_index</span>
    <span class="k">return</span> <span class="kc">None</span></div>


<div class="viewcode-block" id="fix_gov_indexes"><a class="viewcode-back" href="../../../generated_api/nlp_architect.common.html#nlp_architect.common.core_nlp_doc.fix_gov_indexes">[docs]</a><span class="k">def</span> <span class="nf">fix_gov_indexes</span><span class="p">(</span><span class="n">merged_punct_sentence</span><span class="p">,</span> <span class="n">sentence</span><span class="p">):</span>
    <span class="k">for</span> <span class="n">merged_token</span> <span class="ow">in</span> <span class="n">merged_punct_sentence</span><span class="p">:</span>
        <span class="n">tok_gov</span> <span class="o">=</span> <span class="n">merged_token</span><span class="p">[</span><span class="s2">&quot;gov&quot;</span><span class="p">]</span>
        <span class="k">if</span> <span class="n">tok_gov</span> <span class="o">==</span> <span class="o">-</span><span class="mi">1</span><span class="p">:</span>  <span class="c1"># gov is root</span>
            <span class="n">merged_token</span><span class="p">[</span><span class="s2">&quot;gov&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="o">-</span><span class="mi">1</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="n">orig_gov</span> <span class="o">=</span> <span class="n">sentence</span><span class="p">[</span><span class="n">tok_gov</span><span class="p">]</span>
            <span class="n">correct_index</span> <span class="o">=</span> <span class="n">find_correct_index</span><span class="p">(</span><span class="n">orig_gov</span><span class="p">,</span> <span class="n">merged_punct_sentence</span><span class="p">)</span>
            <span class="n">merged_token</span><span class="p">[</span><span class="s2">&quot;gov&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">correct_index</span></div>


<div class="viewcode-block" id="merge_punctuation"><a class="viewcode-back" href="../../../generated_api/nlp_architect.common.html#nlp_architect.common.core_nlp_doc.merge_punctuation">[docs]</a><span class="k">def</span> <span class="nf">merge_punctuation</span><span class="p">(</span><span class="n">sentence</span><span class="p">):</span>
    <span class="n">merged_punct_sentence</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="n">tmp_punct_text</span> <span class="o">=</span> <span class="kc">None</span>
    <span class="n">punct_text</span> <span class="o">=</span> <span class="kc">None</span>
    <span class="n">last_merged_punct_index</span> <span class="o">=</span> <span class="o">-</span><span class="mi">1</span>
    <span class="k">for</span> <span class="n">tok_index</span><span class="p">,</span> <span class="n">token</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">sentence</span><span class="p">):</span>
        <span class="k">if</span> <span class="n">token</span><span class="p">[</span><span class="s2">&quot;rel&quot;</span><span class="p">]</span> <span class="o">==</span> <span class="s2">&quot;punct&quot;</span><span class="p">:</span>
            <span class="n">punct_text</span> <span class="o">=</span> <span class="n">token</span><span class="p">[</span><span class="s2">&quot;text&quot;</span><span class="p">]</span>
            <span class="k">if</span> <span class="n">tok_index</span> <span class="o">&lt;</span> <span class="mi">1</span><span class="p">:</span>  <span class="c1"># this is the first tok - append to the next token</span>
                <span class="n">tmp_punct_text</span> <span class="o">=</span> <span class="n">punct_text</span>
            <span class="k">else</span><span class="p">:</span>  <span class="c1"># append to the previous token</span>
                <span class="n">merge_punct_tok</span><span class="p">(</span><span class="n">merged_punct_sentence</span><span class="p">,</span> <span class="n">last_merged_punct_index</span><span class="p">,</span> <span class="n">punct_text</span><span class="p">,</span> <span class="kc">False</span><span class="p">)</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="n">merged_punct_sentence</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">token</span><span class="p">)</span>
            <span class="n">last_merged_punct_index</span> <span class="o">=</span> <span class="n">last_merged_punct_index</span> <span class="o">+</span> <span class="mi">1</span>
            <span class="k">if</span> <span class="n">tmp_punct_text</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
                <span class="n">merge_punct_tok</span><span class="p">(</span><span class="n">merged_punct_sentence</span><span class="p">,</span> <span class="n">last_merged_punct_index</span><span class="p">,</span> <span class="n">punct_text</span><span class="p">,</span> <span class="kc">True</span><span class="p">)</span>
                <span class="n">tmp_punct_text</span> <span class="o">=</span> <span class="kc">None</span>
    <span class="k">return</span> <span class="n">merged_punct_sentence</span></div>


<div class="viewcode-block" id="CoreNLPDoc"><a class="viewcode-back" href="../../../generated_api/nlp_architect.common.html#nlp_architect.common.core_nlp_doc.CoreNLPDoc">[docs]</a><span class="k">class</span> <span class="nc">CoreNLPDoc</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;Object for core-components (POS, Dependency Relations, etc).</span>

<span class="sd">    Attributes:</span>
<span class="sd">        _doc_text: the doc text</span>
<span class="sd">        _sentences: list of sentences, each word in a sentence is</span>
<span class="sd">            represented by a dictionary, structured as follows: {&#39;start&#39;: (int), &#39;len&#39;: (int),</span>
<span class="sd">            &#39;pos&#39;: (str), &#39;ner&#39;: (str), &#39;lemma&#39;: (str), &#39;gov&#39;: (int), &#39;rel&#39;: (str)}</span>
<span class="sd">    &quot;&quot;&quot;</span>

    <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">doc_text</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span><span class="p">,</span> <span class="n">sentences</span><span class="p">:</span> <span class="nb">list</span> <span class="o">=</span> <span class="kc">None</span><span class="p">):</span>
        <span class="k">if</span> <span class="n">sentences</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
            <span class="n">sentences</span> <span class="o">=</span> <span class="p">[]</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">_doc_text</span> <span class="o">=</span> <span class="n">doc_text</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">_sentences</span> <span class="o">=</span> <span class="n">sentences</span>

    <span class="nd">@property</span>
    <span class="k">def</span> <span class="nf">doc_text</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_doc_text</span>

    <span class="nd">@doc_text</span><span class="o">.</span><span class="n">setter</span>
    <span class="k">def</span> <span class="nf">doc_text</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">val</span><span class="p">):</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">_doc_text</span> <span class="o">=</span> <span class="n">val</span>

    <span class="nd">@property</span>
    <span class="k">def</span> <span class="nf">sentences</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_sentences</span>

    <span class="nd">@sentences</span><span class="o">.</span><span class="n">setter</span>
    <span class="k">def</span> <span class="nf">sentences</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">val</span><span class="p">):</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">_sentences</span> <span class="o">=</span> <span class="n">val</span>

<div class="viewcode-block" id="CoreNLPDoc.decoder"><a class="viewcode-back" href="../../../generated_api/nlp_architect.common.html#nlp_architect.common.core_nlp_doc.CoreNLPDoc.decoder">[docs]</a>    <span class="nd">@staticmethod</span>
    <span class="k">def</span> <span class="nf">decoder</span><span class="p">(</span><span class="n">obj</span><span class="p">):</span>
        <span class="k">if</span> <span class="s2">&quot;_doc_text&quot;</span> <span class="ow">in</span> <span class="n">obj</span> <span class="ow">and</span> <span class="s2">&quot;_sentences&quot;</span> <span class="ow">in</span> <span class="n">obj</span><span class="p">:</span>
            <span class="k">return</span> <span class="n">CoreNLPDoc</span><span class="p">(</span><span class="n">obj</span><span class="p">[</span><span class="s2">&quot;_doc_text&quot;</span><span class="p">],</span> <span class="n">obj</span><span class="p">[</span><span class="s2">&quot;_sentences&quot;</span><span class="p">])</span>
        <span class="k">return</span> <span class="n">obj</span></div>

    <span class="k">def</span> <span class="fm">__repr__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">pretty_json</span><span class="p">()</span>

    <span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="fm">__repr__</span><span class="p">()</span>

    <span class="k">def</span> <span class="fm">__iter__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">sentences</span><span class="o">.</span><span class="fm">__iter__</span><span class="p">()</span>

    <span class="k">def</span> <span class="fm">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sentences</span><span class="p">)</span>

<div class="viewcode-block" id="CoreNLPDoc.json"><a class="viewcode-back" href="../../../generated_api/nlp_architect.common.html#nlp_architect.common.core_nlp_doc.CoreNLPDoc.json">[docs]</a>    <span class="k">def</span> <span class="nf">json</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;Returns json representations of the object.&quot;&quot;&quot;</span>
        <span class="k">return</span> <span class="n">json</span><span class="o">.</span><span class="n">dumps</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="vm">__dict__</span><span class="p">)</span></div>

<div class="viewcode-block" id="CoreNLPDoc.pretty_json"><a class="viewcode-back" href="../../../generated_api/nlp_architect.common.html#nlp_architect.common.core_nlp_doc.CoreNLPDoc.pretty_json">[docs]</a>    <span class="k">def</span> <span class="nf">pretty_json</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;Returns pretty json representations of the object.&quot;&quot;&quot;</span>
        <span class="k">return</span> <span class="n">json</span><span class="o">.</span><span class="n">dumps</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="vm">__dict__</span><span class="p">,</span> <span class="n">indent</span><span class="o">=</span><span class="mi">4</span><span class="p">)</span></div>

<div class="viewcode-block" id="CoreNLPDoc.sent_text"><a class="viewcode-back" href="../../../generated_api/nlp_architect.common.html#nlp_architect.common.core_nlp_doc.CoreNLPDoc.sent_text">[docs]</a>    <span class="k">def</span> <span class="nf">sent_text</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">i</span><span class="p">):</span>
        <span class="n">parsed_sent</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">sentences</span><span class="p">[</span><span class="n">i</span><span class="p">]</span>
        <span class="n">first_tok</span><span class="p">,</span> <span class="n">last_tok</span> <span class="o">=</span> <span class="n">parsed_sent</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">parsed_sent</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">doc_text</span><span class="p">[</span><span class="n">first_tok</span><span class="p">[</span><span class="s2">&quot;start&quot;</span><span class="p">]</span> <span class="p">:</span> <span class="n">last_tok</span><span class="p">[</span><span class="s2">&quot;start&quot;</span><span class="p">]</span> <span class="o">+</span> <span class="n">last_tok</span><span class="p">[</span><span class="s2">&quot;len&quot;</span><span class="p">]]</span></div>

<div class="viewcode-block" id="CoreNLPDoc.sent_iter"><a class="viewcode-back" href="../../../generated_api/nlp_architect.common.html#nlp_architect.common.core_nlp_doc.CoreNLPDoc.sent_iter">[docs]</a>    <span class="k">def</span> <span class="nf">sent_iter</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="k">for</span> <span class="n">parsed_sent</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">sentences</span><span class="p">:</span>
            <span class="n">first_tok</span><span class="p">,</span> <span class="n">last_tok</span> <span class="o">=</span> <span class="n">parsed_sent</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">parsed_sent</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
            <span class="n">sent_text</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">doc_text</span><span class="p">[</span><span class="n">first_tok</span><span class="p">[</span><span class="s2">&quot;start&quot;</span><span class="p">]</span> <span class="p">:</span> <span class="n">last_tok</span><span class="p">[</span><span class="s2">&quot;start&quot;</span><span class="p">]</span> <span class="o">+</span> <span class="n">last_tok</span><span class="p">[</span><span class="s2">&quot;len&quot;</span><span class="p">]]</span>
            <span class="k">yield</span> <span class="n">sent_text</span><span class="p">,</span> <span class="n">parsed_sent</span></div>

<div class="viewcode-block" id="CoreNLPDoc.brat_doc"><a class="viewcode-back" href="../../../generated_api/nlp_architect.common.html#nlp_architect.common.core_nlp_doc.CoreNLPDoc.brat_doc">[docs]</a>    <span class="k">def</span> <span class="nf">brat_doc</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;Returns doc adapted to BRAT expected input.&quot;&quot;&quot;</span>
        <span class="n">doc</span> <span class="o">=</span> <span class="p">{</span><span class="s2">&quot;text&quot;</span><span class="p">:</span> <span class="s2">&quot;&quot;</span><span class="p">,</span> <span class="s2">&quot;entities&quot;</span><span class="p">:</span> <span class="p">[],</span> <span class="s2">&quot;relations&quot;</span><span class="p">:</span> <span class="p">[]}</span>
        <span class="n">tok_count</span> <span class="o">=</span> <span class="mi">0</span>
        <span class="n">rel_count</span> <span class="o">=</span> <span class="mi">1</span>
        <span class="k">for</span> <span class="n">sentence</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">sentences</span><span class="p">:</span>
            <span class="n">sentence_start</span> <span class="o">=</span> <span class="n">sentence</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="s2">&quot;start&quot;</span><span class="p">]</span>
            <span class="n">sentence_end</span> <span class="o">=</span> <span class="n">sentence</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">][</span><span class="s2">&quot;start&quot;</span><span class="p">]</span> <span class="o">+</span> <span class="n">sentence</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">][</span><span class="s2">&quot;len&quot;</span><span class="p">]</span>
            <span class="n">doc</span><span class="p">[</span><span class="s2">&quot;text&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">doc</span><span class="p">[</span><span class="s2">&quot;text&quot;</span><span class="p">]</span> <span class="o">+</span> <span class="s2">&quot;</span><span class="se">\n</span><span class="s2">&quot;</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">doc_text</span><span class="p">[</span><span class="n">sentence_start</span><span class="p">:</span><span class="n">sentence_end</span><span class="p">]</span>
            <span class="n">token_offset</span> <span class="o">=</span> <span class="n">tok_count</span>

            <span class="k">for</span> <span class="n">token</span> <span class="ow">in</span> <span class="n">sentence</span><span class="p">:</span>
                <span class="n">start</span> <span class="o">=</span> <span class="n">token</span><span class="p">[</span><span class="s2">&quot;start&quot;</span><span class="p">]</span>
                <span class="n">end</span> <span class="o">=</span> <span class="n">start</span> <span class="o">+</span> <span class="n">token</span><span class="p">[</span><span class="s2">&quot;len&quot;</span><span class="p">]</span>
                <span class="n">doc</span><span class="p">[</span><span class="s2">&quot;entities&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">([</span><span class="s2">&quot;T&quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">tok_count</span><span class="p">),</span> <span class="n">token</span><span class="p">[</span><span class="s2">&quot;pos&quot;</span><span class="p">],</span> <span class="p">[[</span><span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="p">]]])</span>

                <span class="k">if</span> <span class="n">token</span><span class="p">[</span><span class="s2">&quot;gov&quot;</span><span class="p">]</span> <span class="o">!=</span> <span class="o">-</span><span class="mi">1</span> <span class="ow">and</span> <span class="n">token</span><span class="p">[</span><span class="s2">&quot;rel&quot;</span><span class="p">]</span> <span class="o">!=</span> <span class="s2">&quot;punct&quot;</span><span class="p">:</span>
                    <span class="n">doc</span><span class="p">[</span><span class="s2">&quot;relations&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span>
                        <span class="p">[</span>
                            <span class="n">rel_count</span><span class="p">,</span>
                            <span class="n">token</span><span class="p">[</span><span class="s2">&quot;rel&quot;</span><span class="p">],</span>
                            <span class="p">[</span>
                                <span class="p">[</span><span class="s2">&quot;&quot;</span><span class="p">,</span> <span class="s2">&quot;T&quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">token_offset</span> <span class="o">+</span> <span class="n">token</span><span class="p">[</span><span class="s2">&quot;gov&quot;</span><span class="p">])],</span>
                                <span class="p">[</span><span class="s2">&quot;&quot;</span><span class="p">,</span> <span class="s2">&quot;T&quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">tok_count</span><span class="p">)],</span>
                            <span class="p">],</span>
                        <span class="p">]</span>
                    <span class="p">)</span>
                    <span class="n">rel_count</span> <span class="o">+=</span> <span class="mi">1</span>
                <span class="n">tok_count</span> <span class="o">+=</span> <span class="mi">1</span>
        <span class="n">doc</span><span class="p">[</span><span class="s2">&quot;text&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">doc</span><span class="p">[</span><span class="s2">&quot;text&quot;</span><span class="p">][</span><span class="mi">1</span><span class="p">:]</span>
        <span class="k">return</span> <span class="n">doc</span></div>

<div class="viewcode-block" id="CoreNLPDoc.displacy_doc"><a class="viewcode-back" href="../../../generated_api/nlp_architect.common.html#nlp_architect.common.core_nlp_doc.CoreNLPDoc.displacy_doc">[docs]</a>    <span class="k">def</span> <span class="nf">displacy_doc</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;Return doc adapted to displacyENT expected input.&quot;&quot;&quot;</span>
        <span class="n">doc</span> <span class="o">=</span> <span class="p">[]</span>
        <span class="k">for</span> <span class="n">sentence</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">sentences</span><span class="p">:</span>
            <span class="n">sentence_doc</span> <span class="o">=</span> <span class="p">{</span><span class="s2">&quot;arcs&quot;</span><span class="p">:</span> <span class="p">[],</span> <span class="s2">&quot;words&quot;</span><span class="p">:</span> <span class="p">[]}</span>
            <span class="c1"># Merge punctuation:</span>
            <span class="n">merged_punct_sentence</span> <span class="o">=</span> <span class="n">merge_punctuation</span><span class="p">(</span><span class="n">sentence</span><span class="p">)</span>
            <span class="n">fix_gov_indexes</span><span class="p">(</span><span class="n">merged_punct_sentence</span><span class="p">,</span> <span class="n">sentence</span><span class="p">)</span>
            <span class="k">for</span> <span class="n">tok_index</span><span class="p">,</span> <span class="n">token</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">merged_punct_sentence</span><span class="p">):</span>
                <span class="n">sentence_doc</span><span class="p">[</span><span class="s2">&quot;words&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">({</span><span class="s2">&quot;text&quot;</span><span class="p">:</span> <span class="n">token</span><span class="p">[</span><span class="s2">&quot;text&quot;</span><span class="p">],</span> <span class="s2">&quot;tag&quot;</span><span class="p">:</span> <span class="n">token</span><span class="p">[</span><span class="s2">&quot;pos&quot;</span><span class="p">]})</span>
                <span class="n">dep_tok</span> <span class="o">=</span> <span class="n">tok_index</span>
                <span class="n">gov_tok</span> <span class="o">=</span> <span class="n">token</span><span class="p">[</span><span class="s2">&quot;gov&quot;</span><span class="p">]</span>
                <span class="n">direction</span> <span class="o">=</span> <span class="s2">&quot;left&quot;</span>
                <span class="n">arc_start</span> <span class="o">=</span> <span class="n">dep_tok</span>
                <span class="n">arc_end</span> <span class="o">=</span> <span class="n">gov_tok</span>
                <span class="k">if</span> <span class="n">dep_tok</span> <span class="o">&gt;</span> <span class="n">gov_tok</span><span class="p">:</span>
                    <span class="n">direction</span> <span class="o">=</span> <span class="s2">&quot;right&quot;</span>
                    <span class="n">arc_start</span> <span class="o">=</span> <span class="n">gov_tok</span>
                    <span class="n">arc_end</span> <span class="o">=</span> <span class="n">dep_tok</span>
                <span class="k">if</span> <span class="n">token</span><span class="p">[</span><span class="s2">&quot;gov&quot;</span><span class="p">]</span> <span class="o">!=</span> <span class="o">-</span><span class="mi">1</span> <span class="ow">and</span> <span class="n">token</span><span class="p">[</span><span class="s2">&quot;rel&quot;</span><span class="p">]</span> <span class="o">!=</span> <span class="s2">&quot;punct&quot;</span><span class="p">:</span>
                    <span class="n">sentence_doc</span><span class="p">[</span><span class="s2">&quot;arcs&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span>
                        <span class="p">{</span>
                            <span class="s2">&quot;dir&quot;</span><span class="p">:</span> <span class="n">direction</span><span class="p">,</span>
                            <span class="s2">&quot;label&quot;</span><span class="p">:</span> <span class="n">token</span><span class="p">[</span><span class="s2">&quot;rel&quot;</span><span class="p">],</span>
                            <span class="s2">&quot;start&quot;</span><span class="p">:</span> <span class="n">arc_start</span><span class="p">,</span>
                            <span class="s2">&quot;end&quot;</span><span class="p">:</span> <span class="n">arc_end</span><span class="p">,</span>
                        <span class="p">}</span>
                    <span class="p">)</span>
            <span class="n">doc</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">sentence_doc</span><span class="p">)</span>
        <span class="k">return</span> <span class="n">doc</span></div></div>
</pre></div>

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